Paper
Dominating Sets-Based Approach for Maximizing Lifetime of IoT-Based Heterogeneous WSNs Enabled Sustainable Smart City Applications
Published 2024 · B. Alwasel, Ahmed Salim, A. Khedr
IEEE Access
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Abstract
The versatility and diverse applications of IoT-based Heterogeneous WSN (HWSN) technologies make them valuable tools for achieving sustainability goals in Sustainable Smart Cities (SSCs). Proper management of underlying heterogeneous architecture is crucial for the successful operation of smart applications. To prolong the WSN’s lifespan and avoid failures, effective energy management is essential. Although researchers are continually exploring heterogeneity in WSN, it gets more and more important to create cost-effective paradigms that cover multiple facets of SSC while ensuring their stability and reliability. The concept of Dominating Sets (DS) in a graph can be leveraged to minimize resource utilization in WSNs by arranging nodes into disjoint DS, with only one set executing duties at any given time. In this work, we propose a novel technique for IoT-based HWSNs-enabled SSC, called EADDSA, utilizing the DS concept to plan the sleep-and-awake scheme for heterogeneous nodes, based on their resource capabilities. We propose a new algorithm, called the Energy Attentive Algorithm (EAA), to find disjoint DSs that are energy-aware. EAA algorithm attentively tries to form the set that maximizes lifespan while adhering to DS conditions in each iteration. EADDSA further incorporates an effective DS scheduling strategy to enhance the HWSN lifetime by establishing operational guidelines for each round, taking into account the estimated lifetimes and the designated number of working rounds for each DS. This enables efficient allocation of data sensing and gathering tasks across the network minimizes resource usage, and extends network lifetime.
The EADDSA technique optimizes IoT-based heterogeneous WSNs in Sustainable Smart Cities by minimizing resource usage and extending network lifetime through efficient data allocation and scheduling strategies.
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